Profesor Madya Ts. Dr. Mohd. Hanafi Bin Ahmad Hijazi
Profesor Madya Ts. Dr. Mohd. Hanafi Bin Ahmad Hijazi
Fakulti Komputeran Dan Informatik · Fakulti Komputeran Dan Informatik, UMS
hanafi@ums.edu.my
Summary

Profesor Madya Ts. Dr. Mohd. Hanafi Bin Ahmad Hijazi is a distinguished researcher at Fakulti Komputeran Dan Informatik, University Malaysia Sabah. Their research focuses on Data mining, prediction, image mining, sentiment analysis, medical image analysis .

As a member of Fakulti Komputeran Dan Informatik, they contribute significantly to the academic and research community at UMS through their expertise and dedication to advancing knowledge in their field.

Profesor Madya Ts. Dr. Mohd. Hanafi Bin Ahmad Hijazi holds Doktor Falsafah from Liverpool University, Liverpool,UK , among other qualifications, and has established themselves as a respected expert in their field.

Education
Doktor Falsafah
Sarjana Sains (sains Komputer)
Sarjana Muda Sains (komputer)
Stats
Publications:
109
Projects:
44
Grants:
RM 7,078,065.00
Scopus Metrics
Scopus Author ID:
57211412089
H-Index:
19
Documents:
87
Citations:
1,370
Research Interests
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Deep Learning for Machine Learning
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Natural Language Processing (Including Machine Translation, Sentiment Analysis, Text to Speech (TtS), Speech to Text (StT))
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Digital Image Processing Algorithm and Techniques
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Pattern and Image Recognition
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Data Preparation and Exploration
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Data Mining
Latest Grants
Development Of An Automated Live-bird Counter
Pembangunan Platform Pendidikan, Penilaian Dan Pemantauan Esg (esg-eamp)
Petronas Advanced Analytics Framework For Resource Optimization (petro-afro Framework): Driving Operational Excellence Through Data Science And Artificial Intelligence
Integrated Multi-hop Transceiver Scavenging System
Formulating A Spectrally Adapted One-stage Detection Algorithm For Assessing Beef Cattle Health With Pseudo-rgb And Multispectral Bands
Latest Publications
Multitask Deep Learning For Sentiment Analysis With Sarcasm Detection In Bilingual Code-mixed Social Media Content
A Comparative Study Of Segmentation Techniques For Automated Fish Counting
Empowering Socio-economic Development By Addressing Poverty Challenges In Sabah's Developing Districts
Evaluation Of A Deep Learning System For Pulmonary Tuberculosis Detection Via Chest Radiographs: A Quasi-experimental Study In Sabah
Enhancing Bone Fracture Detection In Medical Imaging: Implementing Transfer Learning And Adversarial Training
Administrative Positions
Fakulti Komputeran Dan Informatik